Abstract PD14-05: PD14-05 Prospective longitudinal validation of a breast cancer risk prediction model in a cohort of 130,058 women
Authors: Brent Mabey, Elisha Hughes, Braden Probst, Holly J. Pederson, Timothy Simmons, Brian Morris, Brooke Hullinger, Susan Domchek, Charis Eng, Monique Gary, Jennifer Klemp, Semanti Mukherjee, Vijai Joseph, Kenneth Offit, Olufunmilayo I. Olopade, Sandhya Pruthi, Allison W. Kurian, Mark E. Robson, Pat Whitworth, Susanne Wagner, Jerry Lanchbury, Thomas Slavin, Alexander Gutin
Journal: Cancer Research (2023)

Abstract Background: Personalized breast cancer (BC) risk assessment depends on known traditional risk factors, specific germline mutations, and genome-wide polygenic risk scores (PRS). PRS explains a substantial proportion of genetic BC susceptibility. Accuracy of BC risk prediction may be improved by combining a PRS with traditional risk factors. We recently developed and validated a 149-SNP PRS for women of diverse ancestries using ancestry-informative genetic markers and combined this with version 7 of the Tyrer-Cuzick (TC) model to generate a Combined Risk Score (CRS). Here, we describe a pre-specified prospective longitudinal clinical validation of CRS as a predictor of BC risk. Methods: Women in the U.S. who were referred for clinical genetic testing between January 2017 and February 2019 were matched to medical and hospital claims in an anonymized dataset. Women with a pathogenic mutation in a BC-related gene were excluded from analysis. Follow-up began 4 months after testing and extended to the earliest date of BC diagnosis, censoring at the time of BC preventive treatment, or November 1, 2019. Incident BC events were determined by an ICD10 code of C50.* and confirmed by relevant treatment codes. CRS calibration was evaluated by the ratio of observed (O) to expected (E) incident BCs for the full cohort, and for women split into event-based 5-year CRS risk deciles. Cox proportional hazards models were used to evaluate discriminatory accuracy in terms of hazard ratios (HR) with 95% confidence intervals (CI) and p-values from likelihood ratio chi-squared statistics. Kaplan-Meier analysis was used to examine risk for women split into high- or low-risk groups according to a 3% 5-year CRS risk threshold. Results: 130,058 women with 148,349 total patient years met study eligibility criteria and were matched to claims data. Over a median (range) follow-up of 12.1 (4.0-29.5) months, 340 incident BC events were observed. The CRS was well calibrated in the overall cohort with an O/E ratio of 1.11 (95% CI=0.99-1.23) and within deciles of predicted risk (Table). Importantly, in the highest risk decile, the O/E was 0.91 (95% CI=0.63-1.27) with CRS, but 0.67 (95% CI=0.46-0.94) with TC alone, illustrating the superior calibration of CRS. In a Cox model adjusted for age at testing, PRS had an HR per standard deviation (SD) of 1.48 (95% CI=1.33-1.64, p=2.55×10-13); the HR/SD was 1.43 (95% CI=1.29-1.59, p=1.61×10-11) after adjusting for family history. In a bivariate analysis using both CRS and TC to predict time to BC, CRS added significantly to the model after accounting for TC (HR/SD=2.89, 95% CI=2.12-3.94, p=1.20×10-11), whereas TC did not add significant information after accounting for CRS. 15,986 (12.3%) women were above the CRS high-risk threshold, including 123 with events. A total of 10,248 (7.9%) women were reclassified by the CRS model compared to the TC model. Among women who were classified as high-risk by TC, 32.6% were reclassified as low-risk by CRS; among those classified as low-risk by TC, 4.3% were reclassified as high-risk by CRS. The CRS high-risk group experienced events at over three times the rate of the low-risk group (HR=3.75, 95% CI=3.00-4.68, p=6.39×10-27). Conclusion: The CRS was well-calibrated in predicting BC and significantly improved upon a traditional risk factor model. Clinical use of the CRS may lead to improved BC prevention and screening strategies. Table: Absolute risk calibration by 5-year risk decile Incidence is reported per 1,000 women-years. 34 breast cancers were observed per decile. Citation Format: Brent Mabey, Elisha Hughes, Braden Probst, Holly J. Pederson, Timothy Simmons, Brian Morris, Brooke Hullinger, Susan Domchek, Charis Eng, Monique Gary, Jennifer Klemp, Semanti Mukherjee, Vijai Joseph, Kenneth Offit, Olufunmilayo I. Olopade, Sandhya Pruthi, Allison W. Kurian, Mark E. Robson, Pat Whitworth, Susanne Wagner, Jerry Lanchbury, Thomas Slavin, Alexander Gutin. PD14-05 Prospective longitudinal validation of a breast cancer risk prediction model in a cohort of 130,058 women [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD14-05.